강원도 북부의 남북 접경지 3개소(서부-철원, 영서-양구, 영동-고성)에서 2023년 5월 11일부터 10월 12일까지 주요 천공성 해충 분류군인 나무좀아과를 대상으로 시기별 발생 양상 및 4가지 유인제(Ipsenol, Ipsedienol, Alpha-pinene, Monochamol)별 유인되는 종과 개체수를 조사 하였다. 연구결과, 총 26속 45종 7,743개체를 확인하였다. 확인한 종 중, 15종이 모든 조사지역에서 공통적으로 발생하고, 2종(암브로시아나무 좀, 왕녹나무좀)이 모든 조사지에서의 우점종으로 확인되었으며, 4종(오리나무좀, 붉은목나무좀, 여름나무좀, 암브로시아나무좀)이 조사기간(5 월~10월) 중 지속적으로 발생하는 것으로 확인되었다. 지역적으로는 가장 다양한 식물종들로 혼합림을 구성하고 있는 양구지역에서 총 36종 2,840개체가 확인되어 다른 두 조사지에서보다 다양하고 많은 개체가 확인되었다. 각 조사지에서 유인제별 확인한 종수는 유의미한 차이를 보이 지 않았으며 개체수면에서 철원에서는 Monochamol, 양구에서는 Ipsedienol, 고성에서는 Ipsenol 유인제에서 가장 많은 개체가 확인되었다.

총담관결석의 치료는 내시경역행담췌관조영술을 시행하여 결석을 제거하는 것이 표준적인 방법이며 내시경유두부 괄약근절개술 및 내시경유두부풍선확장술을 시행한 후 바스켓 및 풍선도관, 기계석 쇄석술 등의 여러가지 방법을 사용하여 그 성공률은 90% 이상으로 알려져 있다. 그러나 일부 거대담석이나 담도협착이 동반된 경우 등에서는 담석의 제거에 실패하는 경우가 있다. 본 저자들은 방사선 비투과성 담석에 대해서 일반적인 담석제거를 위한 방법을 사용한 후에도 담석제거에 실패하고 기계적 쇄석술을 시행하던 중 바스켓의 철선이 끊어지면서 담석과 함께 총담관 내에 잔류하게 된 환자에서 체외충격파 쇄석술을 시행하여 담석을 파쇄한 후 담석의 제거에 성공하였던 증례를 문헌고찰과 함께 보고한다.

This study was conducted to provide basic data on the antioxidant activity, inhibition of adipocyte differentiation and reactive oxygen species (ROS) production of a mixture of Brassica juncea extract (BJE) and fermented black rice fraction (BRF). We investigated the total phenol content, total flavonoid content, antioxidant effects (DPPH radical scavenging, ABTS radical scavenging, reducing power, FRAP and ORAC assay) and anti-obesity activity of the mixture in 3T3-L1 cells. Our results showed that the total phenol and flavonoid content increased with increasing BRF mixture ratio. The antioxidant activity increased as the BRF mixture ratio increased. In addition, BJE and BRF mixtures did not show any cytotoxicity during the 3T3-L1 differentiation period. During adipocyte differentiation, BJE and BRF mixtures significantly inhibited lipid accumulation and ROS production compared to the control group. These results warrant further experiments to develop an anti-obesity functional food using a mixture of BJE and BRF.

This study aimed to confirm the importance ratio of climate and management variables on production of orchardgrass in Korea (1982―2014). For the climate, the mean temperature in January (MTJ, ℃), lowest temperature in January (LTJ, ℃), growing days 0 to 5 (GD 1, day), growing days 5 to 25 (GD 2, day), Summer depression days (SSD, day), rainfall days (RD, day), accumulated rainfall (AR, mm), and sunshine duration (SD, hr) were considered. For the management, the establishment period (EP, 0―6 years) and number of cutting (NC, 2nd―5th) were measured. The importance ratio on production of orchardgrass was estimated using the neural network model with the perceptron method. It was performed by SPSS 26.0 (IBM Corp., Chicago). As a result, EP was the most important variable (100%), followed by RD (82.0%), AR (79.1%), NC (69.2%), LTJ (66.2%), GD 2 (63.3%), GD 1 (61.6%), SD (58.1%), SSD (50.8%) and MTJ (41.8%). It implies that EP, RD, AR, and NC were more important than others. Since the annual rainfall in Korea is exceed the required amount for the growth and development of orchardgrass, the damage caused by heavy rainfall exceeding the appropriate level could be reduced through drainage management. It means that, when cultivating orchardgrass, factors that can be controlled were relatively important. Although it is difficult to interpret the specific effect of climates on production due to neural networking modeling, in the future, this study is expected to be useful in production prediction and damage estimation by climate change by selecting major factors.

This study aimed to investigate the validation and modify the analytical method to determine quercetin- 3-o-gentiobioside and isoquercitrin in Abelmoschus esculentus L. Moench for the standardization of ingredients in development of functional health products. The analytical method was validated based on the ICH (International Conference for Harmonization) guidelines to verify the reliability and validity there of on the specificity, linearity, accuracy, precision, detection limit and quantification limit. For the HPLC analysis method, the peak retention time of the index component of the standard solution and the peak retention time of the index component of A. esculentus L. Moench powder sample were consistent with the spectra thereof, confirming the specificity. The calibration curves of quercetin-3-o-gentiobioside and isoquercitrin showed a linearity with a near-one correlation coefficient (0.9999 and 0.9999), indicating the high suitability thereof for the analysis. A. esculentus L. Moench powder sample of a known concentration were prepared with low, medium, and high concentrations of standard substances and were calculated for the precision and accuracy. The precision of quercetin-3-o-gentiobioside and isoquercitrin was confirmed for intraday and daily. As a result, the intra-day precision was found to be 0.50-1.48% and 0.77-2.87%, and the daily precision to be 0.07-3.37% and 0.58-1.37%, implying an excellent precision at level below 5%. As a result of accuracy measurement, the intra-day accuracy of quercetin-3-o-gentiobioside and isoquercitrin was found to be 104.87-109.64% and the daily accuracy thereof was found to be 106.85-109.06%, reflecting high level of accuracy. The detection limits of quercetin-3-o-gentiobioside and isoquercitrin were 0.24 μg/mL and 0.16 μg/mL, respectively, whereas the quantitation limits were 0.71 μg/mL and 0.49 μg/mL, confirming that detection was valid at the low concentrations as well. From the analysis, the established analytical method was proven to be excellent with high level of results from the verification on the specificity, linearity, precision, accuracy, detection limit and quantitation limit thereof. In addition, as a result of analyzing the content of A. esculentus L. Moench powder samples using a validated analytical method, quercetin-3-o-gentiobioside was analyzed to contain 1.49±0.01 mg/dry weight g, while isoquercitrin contained 1.39±0.01 mg/dry weight g. The study was conducted to verify that the simultaneous analysis on quercetin-3-o-gentiobioside and isoquercitrin, the indicators of A. esculentus L. Moench, is a scientifically reliable and suitable analytical method.

This study aimed to analyze causality of climatic factors that affecting the yield of whole crop barley (WCB) by constructing a network within the natural ecosystem via the structural equation model. The WCB dataset (n=316) consisted of data on the forage information and climatic information. The forage information was collected from numerous experimental reports from New Cultivars of Winter Crops (1993-2012) and included details of fresh and dry matter yield, and the year and location of cultivation. The climatic information included details of the daily mean temperature, precipitation, and sunshine duration from the weather information system of the Korea Meteorological Administration. The variables were growing days, accumulated temperature, precipitation, and sunshine duration in the season for the period of seeding to harvesting. The data was collected over 3 consecutive seasons—autumn, winter, and the following spring. We created a causality network depicting the effect of climatic factors on production by structural equation modeling. The results highlight: (i) the differences in the longitudinal effects between autumn and next spring, (ii) the factors that directly affect WCB production, and (iii) the indirect effects by certain factors, via two or more paths. For instance, the indirect effect of precipitation on WCB production in the following spring season via its effect on temperature was remarkable. Based on absolute values, the importance of WCB production in decreasing order was: the following spring temperature (0.45), autumn temperature (0.35), wintering (-0.16), and following spring precipitation (0.04). Therefore, we conclude that other climatic factors indirectly affect production through the final pathway, temperature and growing days in the next spring, in the climate-production network for WCB including temperature, growing days, precipitation and sunshine duration.

본 연구는 기계학습을 통한 수량예측모델을 이용하여 이상기상에 따른 WCM의 DMY 피해량을 산출하기 위한 목적으로 수행하였다. 수량예측모델은 WCM 데이터 및 기상 데이터를 수집 후 가공하여 8가지 기계학습을 통해 제작하였으며 실험지역은 경기도로 선정하였다. 수량예측모델은 기계학습 기법 중 정확성이 가장 높은 DeepCrossing (R2=0.5442, RMSE=0.1769) 기법을 통해 제작하였다. 피해량은 정상기상 및 이상기상의 DMY 예측값 간 차이로 산출하였다. 정상기상에서 WCM의 DMY 예측값은 지역에 따라 차이가 있으나 15,003~17,517 kg/ha 범위로 나타났다. 이상기온, 이상강수량 및 이상풍속에서 WCM의 DMY 예측 값은 지역 및 각 이상기상 수준에 따라 차이가 있었으며 각각 14,947~17,571 kg/ha, 14,986~17,525 kg/ha 및 14,920~17,557 kg/ha 범위로 나타났다. 이상기온, 이상강수량 및 이상풍속에서 WCM의 피해량은 각각 –68~89 kg/ha, -17~17 kg/ha 및 – 112~121 kg/ha 범위로 피해로 판단할 수 없는 수준이었다. WCM의 정확한 피해량을 산출하기 위해서는 수량예측모델에 이용하는 이상기상 데이터 수의 증가가 필요하다.

본 연구는 객토를 한 간척지에서 석고시용 수준이 알팔파의 수량과 사료성분에 미치는 영향을 알아보고자 수행하였다. 실험장소는 간척한지 17~33년 경과된 석문간척지로서 약 70 cm 정도 객토한 토양이었다. 객토에 사용한 흙은 섬토양의 제염을 하지 않은 것 이었다. 처리는 석고를 시용하지 않은 0 ton/ha 구(G0), 석 고를 2 ton/ha(G2) 및 4 ton/ha(G4) 시용한 구로 하였다. 수확은 알팔파가 개화초기(개화 10%)에 도달할 때 1차 수확하였으며 이 후 수확은 약 35일 간격으로 수확을 하였다. 알팔파의 건물수량은 1차 년도는 G2가 G0와 G4보다 유의적으로 높았으며 2차 년도는 처리간 유의적인 차이는 없었으나 G2가 G0와 G4보다 높은 경향을 보였다. G2에서 알팔파의 건물수량이 높은 이유는 토양의 pH 및 EC가 각각 재배가능 및 재배적합 수준이었고 피복도 및 알팔파 식생비율도 높은 것에 기인하였다. 1차 및 2차 년도 모두 석고 처리 간 CP, NDF 및 ADF 함량 및 RFV는 차이가 없었다. 한편 1차 및 2차 년도의 연구결과를 통해서 알팔파 건물수량에 부정적인 영향을 주는 요인은 봄의 가뭄과 여름의 집중된 강수로 나타났다. 이상으로부터 객토 간척지에서 석고 처리는 알팔파의 건물수량을 높이는데 효과적인 것으로 판단되며 2 ton/ha이 적정 수준인 것으로 사료된다.

공주지역에 조림된 리기다소나무 군락에서 국내 대표 수종인 소나무와 방풍림으로 주로 조림되는 곰솔 낙엽의 분해율 및 분해과정에 따른 영양염류의 함량 변화를 파악하였다. 분해 60개월 경과 후 소나무 낙엽과 곰솔 낙엽의 잔존율은 각각 42.12±5.30과 24.79±1.98%로 소나무와 곰솔의 낙엽 분해율은 곰솔 낙엽의 분해가 소나무 낙엽의 분해에 비해 빠르게 일어났다. 60개월 경과 후 소나무 낙엽과 곰솔 낙엽의 분해상수 (k)는 각각 3.02과 3.59로 곰솔 낙엽의 분해상수가 다소 높게 나타났다. 소나무 낙엽의 분해과정에 따른 C/N, C/P 비율은 초기에 각각 14.4, 144.1 이었으나 60개월 경과 후에는 각각 2.26와 40.1로 점차 감소하였으며, 곰솔 낙엽의 경우 초기 C/N, C/P 비율은 각각 14.4와 111.3로 나타났고, 60개월 경과 후에는 각각 3.06와 45.8로 나타났다. 낙엽의 초기 N, P, K, Ca, Mg 함량은 소나무 낙엽에서 각각 3.07, 0.31, 1.51, 16.56, 2.03 mg g-1, 곰솔 낙엽에서 각각 3.02, 0.39, 0.99, 19.55, 1.48 mg g-1로 소나무 낙엽과 곰솔 낙엽의 질소와 인의 함량은 유사하였다. 60 개월 경과 후 N, P, K, Ca, Mg의 잔존율은 소나무 낙엽에서 각각 231.08, 130.13, 35.68, 48.58, 36.03%이었고, 곰솔 낙엽에서 각각 143.91, 74.02, 28.59, 45.08, 44.99%로 나타났다.

Four types of metal oxide semiconductor gas sensor arrays were used to observe the aroma and spoilage odor emitted during the ripening process of plum & banana fruits. All gas sensors showed a high correlation (R=0.82~0.90) with the olfactory. The TGS 2603 sensor showed a high correlation of 0.90 between the odor generated and sensory perception of smell in the process of ripening and decaying fruits. In addition, it showed a very high correlation of 0.91 with the decay rate of the plum sample, and the significance probability through one-way ANOVA was also less than 0.05, which confirmed it as an optimal gas sensor (TGS 2603). Principal component analysis was performed using all the data. The cumulative variability was 99.54%, which could be explained only by two principal components, and the first principal component was 95.11%, which was related to the freshness of the fruit. It was analyzed as fresh fruit in the negative(-) direction and decayed fruit in the positive(+) direction.

This study aimed to determine the trend in dry matter yield (DMY) of a new sorghum-sudangrass hybrid (SSH) in the central inland regions of Korea. The metadata (n=388) were collected from various reports of the experiments examining the adaptability of this new variety conducted by the Rural Development Administration (1988–2013). To determine the trend, the parameters of autoregressive (AR) and moving average (MA) were estimated from correlogram of Autocorrelation function (ACF) and partial ACF (PACF) using time series modeling. The results showed that the trend increased slightly year by year. Furthermore, ARIMA (1, 1, 0) was found to be the optimal model to describe the historical trend. This means that the trend in the DMY of the SSH was associated with changes over the past two years but not with changes from three years ago. Although climatic variables, such as temperature, precipitation, and sunshine were also considered as environmental factors for the annual trends, no clear association was observed between DMY and climates. Therefore, more precise processing and detailed definition of climate considering specific growth stages are required to validate this association. In particular, research on the impact of heavy rainfall and typhoons, which are expected to cause damage in the short term, on DMY trends is ongoing, and the model confirmed in this study is expected to play an important role in studying this aspect. Furthermore, we plan to add the environmental factors such as soil and cultivation management as well as climate to our future studies.

The objective of this study was to access the effect of climate and soil factors on alfalfa dry matter yield (DMY) by the contribution through constructing the yield prediction model in a general linear model considering climate and soil physical variables. The processes of constructing the yield prediction model for alfalfa was performed in sequence of data collection of alfalfa yield, meteorological and soil, preparation, statistical analysis, and model construction. The alfalfa yield prediction model used a multiple regression analysis to select the climate variables which are quantitative data and a general linear model considering the selected climate variables and soil physical variables which are qualitative data. As a result, the growth degree days(GDD) and growing days(GD), and the clay content(CC) were selected as the climate and soil physical variables that affect alfalfa DMY, respectively. The contributions of climate and soil factors affecting alfalfa DMY were 32% (GDD, 21%, GD 11%) and 63%, respectively. Therefore, this study indicates that the soil factor more contributes to alfalfa DMY than climate factor. However, for examming the correct contribution, the factors such as other climate and soil factors, and the cultivation technology factors which were not treated in this study should be considered as a factor in the model for future study.

This study was conducted to analyze the characteristics of odorous components that have been generated from the downtown sewer system based on twenty-three survey items for complex odor and designated offensive odor. As a result of the research, the contribution rates for the causative materials of the odor indicated 73.5% of hydrogen sulfide, 26.0% of methyl mercaptan, 0.4% of dimethyl sulfide, and 0.1% of dimethyl disulfide. The occurrence for the odorous materials according to sampling site revealed data of which contribution rates showed 56.9% of hydrogen sulfide and 36.8% of methyl mercaptan from the combined sewer system in the business district; whereas the combined sewer system in the residential area showed 16.4% of dimethyl sulfide and 4.3% of dimethyl disulfide. The seasonal occurrence rate of the odor materials was observed higher in summer and lower in winter And, the combined sewer system in the business district recorded the highest concentration of 4.61 ppm of hydrogen sulfide among the sampling site. An hourly occurrence rate for the odor materials consistently showed the greatest increase between 11:00 and 14:00 at each location and showed a decreasing tendency afterward.

This study aimed to discuss the optimal seeding and harvesting dates with growing degree days(GDD) via meta-data of whole crop maize(WCM). The raw data (n=3,152) contains cultivation year, cultivars, location, seeding and harvesting dates collected from various reports such as thesis, science journals and research reports (1982-2012). The processing was: recording, screening and modification of errors; Then, the final dataset (n=121) consists of seeding cases (n=29), and harvesting cases (n=92) which were used to detect the optimum. In addition, the optimal periods considering tolerance range and GDD also were estimated. As a result, the optimum seeding and harvesting periods were 14th April ~ 3rd May and 15th August ~ 4th September, respectively; where, their GDDs were 23.7~99.6℃ and 1,328.7~ 1,602.1℃, respectively. These GDDs could be used as a judge standard for selecting the seeding and harvesting dates.